Moving From COVID-19 Mathematical Models to Vaccine Design: Theory, Practice and Experiences

Description

This compendium represents a set of guides to understanding the challenging scientific, epidemiological, clinical, social, and economic phenomenon that is represented by the COVID-19 pandemic. The book explains the mathematical modeling of COVID-19 infection, with emphasis on traditional epidemiological principles. It represents a rigorous, comprehensive and multidisciplinary approach to a complex phenomenon. The chapters take into account the knowledge arising from different disciplines (epidemiology, pathophysiology, immunology, medicine, biology, vaccine development, etc.). It also covers COVID-19 data analysis, giving the reader a perspective of statistics and data science, and includes a discussion about social and economic issues of the pandemic. Each chapter is devoted to a specific topic, and is contributed by experts in epidemiology. Because of its multidisciplinary nature, this book is intended as a reference on mathematical models and basic immunotherapy for COVID-19 for a broad community of readers, from scholars who have scientific training, to general readers who have an interest in the disease. Cover Title Copyright End User License Agreement Contents Foreword I Foreword II Foreword III Preface List of contributors An Approach to COVID-19: Current Results, Perspectives and its Study with Mathematical and Computational Modeling Tools Introduction Importance The COVID-19 Pandemic as a Complex Phenomenon Mathematical and Computational Modeling in Epidemiology Different Perspectives for the Study of the Disease and the COVID-19 Pandemic Action of the Virus at Different Scales of Biological Organization Temporal Evolution of COVID-19 Disease at the Individual Level Temporal Evolution of the COVID-19 Pandemic at the Country Level and at the Global Level; the Role of Human Mobility Collateral Consequences for Human Health, Society and the Economy; Final Comments Mathematical and Computational Modeling of COVID-19: Results and Perspectives Main Characteristics of Forecasting and Compartmental Models and the Basic Assumptions that Support Them Renewal Equations: Another Scheme for the Construction of Compartmental Models Methodology for the Application of Compartmental Models of the SIR-Type What Are Compartmental Epidemiological Models Useful for and What Are Their Limitations? How Are the Components of an Epidemiological Compartmental Model Constructed in Correspondence with the Application It Is Intended for? Some Important Results Obtained on COVID-19 with the Use of Compartmental Mathematical Models Some Pending Issues in the Collection and Analysis of Data and in the Study of the Mathematical Models, Associated with COVID-19 Concluding Remarks Consent for Publication Conflict of Interest Acknowledgements References Epidemiology of COVID-19 Introduction Importance Preliminaries Coronaviruses of Public Health Importance The SARS-CoV-2 Virus Origin and Evolution of the Pandemic International Health Regulations and Mechanisms for Preparing and Responding to Threats to Public Health What Is a Public Health Emergency of International Concern? Global Epidemiological Situation and in Mexico of COVID-19 Transmission Mechanisms and ``Reproduction Number'' (R0) Preventive Measures Concluding Remarks Consent for Publication Conflict of Interest Acknowledgements References COVID-19 Pathophysiology, Clinical Manifestations, and Drug Treatment Introduction Importance Preliminaries Pathophysiology of the Disease Virology Inflammatory Response Thrombotic Phenomena Clinical Manifestations of SARS-CoV-2 Infection Asymptomatic Infection Symptomatic Infection Clinical Manifestations Drug Treatment Convalescent Patient Plasma Remdesivir Baricitinib Anticoagulation and COVID-19 Steroid Use in COVID-19 Tocilizumab Concluding Remarks Consent for Publication Conflict of Interest Acknowledgements References Modelling Epidemics: a Perspective on Mathematical Models and Their Use Introduction Importance Preliminaries Basic Results of the Kermack-McKendrick Model More General Models Modification of the Basic Models Epidemic Curves Epidemic Interactions Concluding Remarks Consent for Publication Conflict of Interest Acknowledgements References Data Science: A Useful Tool for Understanding SARS-CoV-2 Information Facts Introduction Importance Preliminaries Artificial Intelligence: the New Boom General Framework of Data Science Projects The Data Science Workflow Exploratory Data Analysis and Preprocessing Case Study: the Mexican COVID-19 Data The Database Bayesian Networks Decision Trees Concluding Remarks Consent for Publication Conflict of Interest Acknowledgements References Epidemic Progression in a Heterogeneously Distributed Population Introduction Importance Epidemiological Situation Epidemiological Modelling Model Problem for a Heterogeneous Population Basic Reproduction Number Final Size of the Epidemic Maximum Number of Infected Individuals Model with Reinfection Basic Reproduction Number Existence of Endemic Equilibrium Final Size of the Epidemic Multipatch Model Two-Group Single-Patch Model Two-Group n Patch Model Epidemic Progression in Some States in India Epidemic Progression in Maharashtra Epidemic Progression in the Neighboring States Concluding Remarks Consent for Publication Conflict of Interest Acknowledgements References Social Inequalities in COVID-19 Introduction Importance Preamble Preliminaries Context and Health in the Life Course The Right to Health Conceptual Bases for Measuring Social Inequalities Related to Health Common Contexts and Applications of Inequality Measurement Basic Properties and Desirable Attributes for Health Inequality Indices A Basic Taxonomy of Indices to Measure Inequalities bib07053 Indices for Ordered Categories Indices Based on Pairwise Comparisons Indices Based on the Regression Model The Concentration Index (CI) Indices for Non-Ordered Categories Indices Based on Pairwise Comparisons Dispersion Indices Indices Based on the Comparison of Two Probability Distributions Options in Measuring Social Inequalities in Relation to Health COVID-19 and Inequalities. Some Selected Results Concluding Remarks Consent for Publication Conflict of Interest Acknowledgements References Statistical Approaches to Understand COVID-19 Severity and Fatality Introduction Importance Preliminaries Basic Statistics Applied to COVID-19 Severity Confirmed Cases, Severity, and Recovery or Death Burden of COVID-19 Cluster Analysis for Patient Stratification Prediction Models for Severity and Fatality Case-Example: Predictors of COVID-19 Fatality in Cuba Background Materials and Methods Results and Discussion Further Applications of Statistical and Epidemiological Techniques Concluding Remarks Consent for Publication Conflict of Interest Acknowledgements References Understanding the Impact of Cuban Immunotherapy Protocols During COVID-19 Disease: Contributions from Mathematical Modeling and Statistical Approaches Introduction Importance Preliminaries Mathematical Model Presentation Model Assumptions Model Equations Model Results Itolizumab on COVID-19 Preliminary Evidences from the Clinical Practice Concluding Remarks Consent for Publication Conflict of Interest Acknowledgements References Vaccines Against SARS-CoV-2. Eradicating COVID-19 Introduction Importance Preliminaries Vaccine Development Process Fast-Track Procedures for COVID-19 Vaccine Major COVID-19 Vaccine Approaches Original Virus as Vaccine Platform Other Viruses as Vaccine Platform Genetic Material as Vaccine Platform Protein/Peptides Delivered as Subunit Vaccines Concluding Remarks Consent for Publication Conflict of Interest Acknowledgements References Appendix: COVID-19 in charts Subject Index Back Cover